Orc: Open Source Multi-Project Orchestrator for AI Coding Agents
Orc is an open source multi-project orchestrator for Claude Code and other agentic CLIs, built to coordinate AI coding agents across every project on your machine. It uses bash, tmux, and git worktrees to manage multiple instances running in parallel.
Key Features
The tool addresses common problems when running multiple Claude Code instances: merge conflicts, duplicated work, lack of review gates, and token burn on coordination overhead. Orc takes a simpler approach compared to other solutions, using a mental model that maps directly to how real software teams work.
How It Works
You describe the work, and the project orchestrator automatically scouts your codebase, pulling in project context (structure, conventions, existing specs) before planning. It then assembles goals, breaks those into beads (focused work items), and spawns engineers in isolated git worktrees.
Every piece of work goes through a two-tier review loop:
- Short-cycle dev review on each bead before it merges to the goal branch
- Optional long-cycle goal review on the full deliverable before it ships
You control both review types by plugging in your own review tool or describing standards in plain English:
[review.dev]
review_instructions = "Focus on security: check for SQL injection, XSS, and auth bypass."Interface and Compatibility
The tmux session is orchestrated into a managed TUI. Each goal gets its own window with the goal orchestrator on the left and engineers plus ephemeral reviewers stacked on the right. You can see all work in progress, navigate to any agent, and hijack a session to pair with it or take over entirely. Status indicators on every window provide at-a-glance visibility.
Orc is fully compatible with spec-driven development—point it at your specs and the orchestrator works from them.
Technical Details
- Claude Code is the default agent with a first-class adapter (--append-system-prompt for prompt delivery, slash commands install to ~/.claude/commands/orc/)
- Also works with OpenCode, Codex, Gemini CLI, or any custom binary
- YOLO mode skips all confirmation gates but still escalates on merge conflicts and blocked engineers
- Coordination is file-based signals, not agent-to-agent conversation—zero tokens burned on orchestration overhead
- Runtime is bash, tmux, and git
- State is three files
- Setup takes five minutes
The tool is available at https://github.com/spencermarx/orc.
📖 Read the full source: r/ClaudeAI
👀 See Also
ZSE: Open-source LLM inference engine with 3.9-second cold starts
ZSE is an open-source LLM inference engine that reduces 32B model memory requirements from 64GB to 19.3GB VRAM and achieves 3.9-second cold starts for 7B models using a pre-quantized .zse format with memory-mapped weights.
OmniCoder-9B fine-tune shows strong performance for agentic coding on 8GB VRAM systems
A Reddit user tested OmniCoder-9B, a fine-tune of Qwen3.5-9B on Opus traces, with OpenCode and reported 40+ tokens per second speeds using Q4_K_M GGUF quantization at 100k context length on an 8GB VRAM system.
Compass Chrome Extension Adds Navigation Tools to Claude and ChatGPT
A developer built a free Chrome extension called Compass that adds a prompt minimap, sticky scroll headers, session checklists, and prompt builder templates to Claude and ChatGPT interfaces to solve navigation problems in long conversations.
OpenRouter Model Pricing and Intelligence-per-Dollar Analysis
A Reddit user compiled OpenRouter API pricing for 16 AI models and calculated intelligence-per-dollar values, identifying MiMo-V2-Flash as best value at $0.09/M tokens and GPT-5.4 as most intelligent at $2.50/M tokens.